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          机器学习-BI



Week_23
基于流行度的推荐


1.基于流行度的推荐1.1简介什么是基于流行度的推荐？就是推荐模型的建立是围绕计算内容的流行度展开的，也就是说基于流行度推荐的核心就是计算内容的流行度。通熟讲就是什么内容流行度越高，就给用户推荐什么。本质上就是什么内容对用户吸引力高，就给用户推荐什么。那什么是流行度呢？也就是我们通常说的“热度”。我们在各个互联网产品中最常见到基于流行度推
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          机器学习-BI



Week_22
LSH近似最近邻查找


什么是最近邻查找？在推荐系统中，主要分为召回跟排序两个阶段。
召回阶段，基于用户画像及场景数据从海量的视频库（百万级别）中将相关度最高的资源检索出来，作为候选集，召回阶段可以通过“粗糙”的方式召回候选item。排序阶段，基于更加精细的特征对候选集（百级别）进行排序，最终呈现给用户的是很少的一部分数据。在这个ranking阶段，采用更精
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          机器学习-BI



Week_21
CTR预估与Youtube推荐系统


1.CTR推荐算法CTR架构一个典型的CTR流程如下图所示：

如上图，主要包括两大部分：离线部分、在线部分，其中离线部分目标主要是训练出可用模型，而在线部分则考虑模型上线后，性能可能随时间而出现下降，弱出现这种情况，可选择使用Online-Learning来在线更新模型：

离线部分：

数据收集：主要收集和业务相关的
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              2021-07-31
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              <a href="/walker_sue/tags/Wide-Deep/">Wide&Deep</a>
            
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          机器学习-BI



Week_20
因子分解机, libFM与基于邻域的协同过滤


CTR是个啥？点击率(click-through rate,CTR)是点击特定链接的用户与查看页面，电子邮件或广告的用户数量之比。它通常用于衡量某个网站的在线广告活动是否成功，以及电子邮件活动的有效性，是互联网公司进行流量分配的核心依据之一。  
$$CTR = \frac{number ofclick-thr
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        <a href="/walker_sue/2021/07/09/week18-Apriori/">挖掘数据中的关联规则</a>
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          机器学习-BI



Week_18
挖掘数据中的关联规则


1 关联规则基本概念沃尔玛商店的营销人员发现了一个现象：啤酒与尿布的销量在周末总会同时出现增长。他们对这个现象进行了分析和讨论，并在商场内进行观察，他们发现这些顾客有几个共同的特点：

一般是周末出现这种情况。
购买者以已婚男士为主。
他们家中有孩子且不到两岁，有尿不湿的刚需。

从中受到启发，他们对超市的物品摆放位置进行了调整，将啤
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        <a href="/walker_sue/2021/07/03/week17-RS/">商业智能与推荐系统</a>
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          机器学习-BI



Week_17
商业智能与推荐系统


一、推荐系统什么是推荐系统推荐系统是一种 信息过滤 系统，根据用户的历史行为、社交关系、兴趣点给用户推荐适合他们的信息。
算法可以判断用户当前感兴趣的物品或内容。你也可以将它理解为一家只为你而开的商店。店铺里摆放的都是你需要的，或者适合你的商品。那么机器是如何帮你找到适合你的商品呢？这就要用到推荐系统，利用算法拟合用户数据，给用户推荐相
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              2021-07-03
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        <a href="/walker_sue/2021/06/25/week16-VRP/">常见规划问题（四）</a>
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          机器学习-BI


Week_16
常见规划问题（四）


一、VRP问题车辆路径规划问题(Vehicle Routing Problem，VRP)一般指的是：对一系列发货点和收货点，组织调用一定的车辆，安排适当的行车路线，使车辆有序地通过它们，在满足指定的约束条件下（例如：货物的需求量与发货量，交发货时间，车辆容量限制，行驶里程限制，行驶时间限制等），力争实现一定的目标（如车辆空驶总里程最短，运
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              2021-06-25
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        <a href="/walker_sue/2021/06/10/week15-NP3/">常见规划问题（三）</a>
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          机器学习-BI



Week_15
优化算法汇总


优化算法总结1.优化算法简介算法本质是一种按照固定步骤执行的过程。
优化算法也是这样一种过程，是一种根据概率按照固定步骤寻求问题的最优解的过程。与常见的排序算法、寻路算法不同的是，优化算法不具备等幂性，是一种概率算法。算法不断的迭代执行同一步骤直到结束，其流程如下图。

等幂性等幂性即对于同样的输入，输出是相同的。
概率算法概率算法的最大优点
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Week_04
常见规划问题（二）


凸优化问题
参考资料
1.凸优化问题


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Week_13
常见规划问题（一）


1.规划问题的分类
线性规划： 在一组线性约束条件的限制下，求一线性目标函数最大或最小的问题； 
整数规划：当约束条件加强，要求所有的自变量必须是整数时，成为整数规划（特别地，自变量只能为0或1时称为0-1规划）； 
非线性规划：无论是约束条件还是目标函数出现非线性项，那么规划问题就变成了非线性规划； 
多目标规划：在一组约束条件的限制下
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